Modification of Good Tests in Dynamic Contexts: Application to Modeling Intellectual Development of Cadets

An approach to incremental learning of Good Maximally Redundant Diagnostic Tests (GMRTs) is considered. GMRT is a special formal concept in Formal Concept Analysis. Mining GMRTs from data is based on Galois lattice construction. Four situations of learning GMRTs are considered: inserting an object (value) and deleting an object (value). An application to modeling intellectual development of cadets is proposed. We explore two datasets of female medical cadets. First dataset is formed at the moment of admission to academy, and another is formed at the end of second year of learning. Classification attribute (dynamics of cadets’ intellectual development) is based on analysis of psychological questionnaire invented by M.M. Reshetnikov and B.V. Kulagin. Structural model attributes are based on MMPI questionnaire adopted by L.N. Sobchik.